MBL202: Taking Data to the Extreme

As GoPro expands into content networks and launches new products, new challenges have appeared. One of the most critical challenges facing GoPro during this period of rapid growth is their ability to make effective use of massive amounts of data. Every day, GoPro collects increasing amounts of data generated by internet connected consumer devices (smart cameras, smart drones), GoPro mobile apps, GoPro content networks, GoPro e-commerce sales, and social media. This data ranges from raw camera logs to refined and well-structured e-commerce datasets. In the past, it took GoPro months to understand new inbound data and determine how to transform or augment it for analysis. To streamline this process and bridge the gap between tech-savvy engineers and data-savvy analysts, GoPro is creating an analysis loop, which informs product usage trends and product insights. This analysis loop serves a large ecosystem of GoPro executives, product managers, engineers, data scientists, and business analysts through an integrated technology pipeline consisting of Apache Kafka, Apache Spark Streaming, Cloudera’s distribution of Hadoop, and Tableau’s Data Visualization Software as the end user analytical tool. Session sponsored by Tableau Software.